{"citation":{"apa":"Savin, C., &#38; Denève, S. (2014). Spatio-temporal representations of uncertainty in spiking neural networks (Vol. 3, pp. 2024–2032). Presented at the NIPS: Neural Information Processing Systems, Montreal, Canada: Neural Information Processing Systems.","ista":"Savin C, Denève S. 2014. Spatio-temporal representations of uncertainty in spiking neural networks. NIPS: Neural Information Processing Systems vol. 3, 2024–2032.","chicago":"Savin, Cristina, and Sophie Denève. “Spatio-Temporal Representations of Uncertainty in Spiking Neural Networks,” 3:2024–32. Neural Information Processing Systems, 2014.","ieee":"C. Savin and S. Denève, “Spatio-temporal representations of uncertainty in spiking neural networks,” presented at the NIPS: Neural Information Processing Systems, Montreal, Canada, 2014, vol. 3, no. January, pp. 2024–2032.","ama":"Savin C, Denève S. Spatio-temporal representations of uncertainty in spiking neural networks. In: Vol 3. Neural Information Processing Systems; 2014:2024-2032.","mla":"Savin, Cristina, and Sophie Denève. <i>Spatio-Temporal Representations of Uncertainty in Spiking Neural Networks</i>. Vol. 3, no. January, Neural Information Processing Systems, 2014, pp. 2024–32.","short":"C. Savin, S. Denève, in:, Neural Information Processing Systems, 2014, pp. 2024–2032."},"date_created":"2018-12-11T11:53:35Z","month":"01","department":[{"_id":"GaTk"}],"date_published":"2014-01-01T00:00:00Z","user_id":"4435EBFC-F248-11E8-B48F-1D18A9856A87","page":"2024 - 2032","status":"public","year":"2014","publisher":"Neural Information Processing Systems","day":"01","intvolume":"         3","language":[{"iso":"eng"}],"volume":3,"publist_id":"5427","date_updated":"2021-01-12T06:52:40Z","type":"conference","issue":"January","publication_status":"published","abstract":[{"text":"It has been long argued that, because of inherent ambiguity and noise, the brain needs to represent uncertainty in the form of probability distributions. The neural encoding of such distributions remains however highly controversial. Here we present a novel circuit model for representing multidimensional real-valued distributions using a spike based spatio-temporal code. Our model combines the computational advantages of the currently competing models for probabilistic codes and exhibits realistic neural responses along a variety of classic measures. Furthermore, the model highlights the challenges associated with interpreting neural activity in relation to behavioral uncertainty and points to alternative population-level approaches for the experimental validation of distributed representations.","lang":"eng"}],"oa_version":"None","author":[{"first_name":"Cristina","full_name":"Savin, Cristina","last_name":"Savin","id":"3933349E-F248-11E8-B48F-1D18A9856A87"},{"full_name":"Denève, Sophie","first_name":"Sophie","last_name":"Denève"}],"conference":{"end_date":"2014-12-13","start_date":"2014-12-08","name":"NIPS: Neural Information Processing Systems","location":"Montreal, Canada"},"main_file_link":[{"url":"http://papers.nips.cc/paper/5343-spatio-temporal-representations-of-uncertainty-in-spiking-neural-networks.pdf"}],"_id":"1708","title":"Spatio-temporal representations of uncertainty in spiking neural networks","scopus_import":1,"quality_controlled":"1"}